• The KIPS Transactions:PartB
• /
• v.8B no.5
• /
• pp.557-564
• /
• 2001

In general, several moving regions with different motions coexist in a block located on motion boundaries in the block-based motion estimation. In this case the motion compensation error(MCEs) are different with the moving regions. This is inclined to deteriorate the quality of motion compensated images because of the inaccurate motions estimated from the conventional mean absolute error(MAE) based matching function in which the matching error per pixel is accumulate throughout the block. In this paper, we divided a block into the regions according to their motions using the motion information of the spatio-temporally neighboring blocks and calculate the average MCF for each moving mentioned. From the simulation results, we showed the improved performance of the proposed method by comparing the results from other methods such as the full search method and the edge oriented block matching algorithm. Especially, we improved the quality of the motion compensated images of blocks on motion boundaries.

• Journal of Intelligence and Information Systems
• /
• v.12 no.1
• /
• pp.33-41
• /
• 2006

This paper presents a method that automatically recognizes products into model type, which it flows with the conveyor belt. The specific interlaced image are occurred by moving image when we use the NTSC based camera. It is impossible to process interlaced images, so a suitable post-processing is required. For the purpose of this processing, after it remove interlaced images using de-interlacing method, it leads rectangle region of object by thresholding. And then, after rectangle region is separated into several blocks through edge detection, we calculate pixel numbers per each block, re-classify using its average, and classify products into model type. Through experiments, we know that the proposed method represent high classification ratio.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.13 no.4
• /
• pp.91-97
• /
• 2013

A finger-gesture remote controller using the single camera is implemented in this paper, which is base on the recognition of finger number and finger moving direction. Proposed method uses the transformed YCbCr color-difference information to extract the hand region effectively. The number and position of finger are computer by using a double circle tracing method. Specially, a user continuous-command can be performed repeatedly by recognizing the finger-gesture direction of single shape. The position information of finger enables a user command to amplify a same command in the User eXperience. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the our proposed method, after applying to the commercial video player software as a remote controller. As a result, the proposed method showed the average 89% recognition ratio by the user command-mode.

• Journal of Broadcast Engineering
• /
• v.24 no.5
• /
• pp.802-812
• /
• 2019

With the rapid development in the field of unmanned aerial vehicles(UAVs) and drones, higher request to development of a surveillance system for a drone is putting forward. Since surveillance systems with fixed cameras have a limited range, a development of surveillance systems with a moving camera applicable to PTZ(Pan-Tilt-Zoom) cameras is required. Selecting the features for object plays a critical role in tracking, and the object has to be represented by their shapes or appearances. Considering these conditions, in this paper, an object tracking method with optical flow is introduced to track a tiny drone with a moving camera. In addition, a tracking method combined with kalman filter is proposed to track continuously even when tracking is failed. Experiments are tested on sequences which have a target from the minimal 12 pixels to the maximal 56337 pixels, the proposed method achieves average precision of 175% improvement. Also, experimental results show the proposed method tracks a target which has a size of 12pixels.

• Journal of Broadcast Engineering
• /
• v.5 no.2
• /
• pp.281-289
• /
• 2000

While acquiring images, the relative motion between the imaging device and the object scene seriously damages the image quality. This phenomenon is called motion blur. The peak-trace approach, which is our recent previous work, identifies important parameters to characterize the point spread function (PSF) of the blur, given only the blurred image itself. With the peak-trace approach the direction of the motion blur can be extracted regardless of the noise corruption and does not need much Processing time. In this paper stochastic peak-trace approaches are introduced. The erroneous data can be selected through the ML classification, and can be made small through weighting. Therefore the distortion of the direction in the low frequency region can be prevented. Using the linear prediction method, the irregular data are prohibited from being selected as the peak point. The detection of the second peak using the proposed moving average least mean (MALM) method is used in the Identification of the motion extent. The MALM method itself includes a noise removal process, so it is possible to extract the parameters even an environment of heavy noise. In the experiment, we could efficiently restore the degraded image using the information obtained by the proposed algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.43 no.5 s.311
• /
• pp.38-47
• /
• 2006

Conventional classification method uses a single classifier based on shape or motion feature. However this method exhibits a weakness if naively used since the classification performance is highly sensitive to the accuracy of moving region to be detected. The detection accuracy, in turn, depends on the condition of the image background. In this paper, we propose to resolve the drawback and thus strengthen the classification reliability by employing a Bayesian decision fusion and by optimally combining the decisions of three classifiers. The first classifier is based on shape information obtained from Fourier descriptors while the second is based on the shape information obtained from image gradients. The third classifier uses motion information. Our experimental results on the classification Performance of human and vehicle with a static camera in various directions confirm a significant improvement and indicate the superiority of the proposed decision fusion method compared to the conventional Majority Voting and Weight Average Score approaches.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.6
• /
• pp.269-276
• /
• 2006

In this paper, we propose an emotion recognition system that can discriminate human emotional state into neutral or anger from the speech captured by a cellular-phone in real time. In general. the speech through the mobile network contains environment noise and network noise, thus it can causes serious System performance degradation due to the distortion in emotional features of the query speech. In order to minimize the effect of these noise and so improve the system performance, we adopt a simple MA (Moving Average) filter which has relatively simple structure and low computational complexity, to alleviate the distortion in the emotional feature vector. Then a SFS (Sequential Forward Selection) feature optimization method is implemented to further improve and stabilize the system performance. Two pattern recognition method such as k-NN and SVM is compared for emotional state classification. The experimental results indicate that the proposed method provides very stable and successful emotional classification performance such as 86.5%. so that it will be very useful in application areas such as customer call-center.

• KIEAE Journal
• /
• v.13 no.2
• /
• pp.67-76
• /
• 2013

The purpose of this study is to analyze the accessibility to the place for outdoor exercise. For that, the departure (resident) location of the users of outdoor exercise equipment within 12 parks in Seoul have been investigated. A total of 1,733 people have been surveyed during the two-week period between Aug.2 and Aug. 15 and 815 cases were analyzed. We also investigated demographic characteristics, access method and related factors such as location, climate and visiting time. The results were coded through ArcGis program and the accessibility to each exercise location, difference in regional accessibility and accessibility characteristics in terms of climate and time have been analyzed. The results are as follows: First, visitors to the Han River start from the places further than the visitors to the streamlines. Second, the average moving distance is longer for the users aged under-60 than for the users aged 60 and over to reach the exercise place. And the average moving distance for visitors to the Han River destination is the longest with 748 meters, followed by 203 meters for general parks and 92 meters for streamline parks, respectively. Third, in each non-waterfront parks, the moving distance by users under-60 was longer by about 230 meters than that by users 60 and over. Fourth, exercisers in the weekend travel more by 244 meters than those during the midweek users to reach the exercise place. Fifth, the number of visitors to the Han River increased in the weekend while visitors to the streamlines decreased in the same period. Sixth, the traveling length for bicycle users is three times as much as that for pedestrian visitors. And the departure locations of bicycle users were more widely distributed.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.22 no.1
• /
• pp.75-85
• /
• 1985

We have studied on the 2-D moving target tracking algorithm satisfying a real-time hardware implementation requirement. In this paper, a fast algorithm is developed based on the operator formulation and the variational algorithm f 10] . Here, we use the directed search for the maximum of the cross-correlation in order to obtain an initial estimate for the variational algorithm and decompose the scene into 16 smaller subblocks and apply the variational algorithm to each subblock sequentially with a new moving area detection method. We call the algorithm subblock based recursive algorithm. Compared with (10) , the ratio of the computational savings obtained from the proposed algorithm is 7 on the average.

• ETRI Journal
• /
• v.37 no.5
• /
• pp.867-876
• /
• 2015

This paper proposes an efficient interference control scheme for vehicular moving networks. The features of the proposed scheme are as follows: radio resources are separated into two resource groups to avoid interference between the cellular and vehicle-to-vehicle (V2V) links; V2V links are able to share the same radio resources for an improvement in the resource efficiency; and vehicles can adaptively adjust their transmission power according to the interference among the V2V links (based on the distributed power control (DPC) scheme derived using the network utility maximization method). The DPC scheme, which is the main feature of the proposed scheme, can improve both the reliability and data rate of a V2V link. Simulation results show that the DPC scheme improves the average signal-to-interference-plus-noise ratio of V2V links by more than 4 dB, and the sum data rate of the V2V links by 15% and 137% compared with conventional schemes.